# Coursebooks

## Probabilities and statistics I

#### Lecturer(s) :

Goldstein Darlene

English

#### Summary

Introduction to notions of probability and basic statistics.

#### Content

• Descriptive statistics
• Combinatorics
• Probability density and cumulative distribution function
• Conditional probability and independence
• Law of total probability, Bayes' rule
• Discrete random variables, expected value and variance
• Discrete laws: binomial, Poisson
• Continuous random variables, expected value and variance
• Continuous laws: uniform, normal, exponential
• Transformations of random variables, standardization
• Joint distributions
• Central Limit Theorem
• Confidence intervals
• Maximum Likelihood estimation
• Introduction to hypothesis testing

#### Learning Outcomes

By the end of the course, the student must be able to:
• Demonstrate understanding of course material
• Apply understanding to exercise/real life scenarios

#### Transversal skills

• Use a work methodology appropriate to the task.

#### Teaching methods

Lectures and group exercises

#### Expected student activities

Students should be prepared to participate in their learning by participating during lecture, asking questions, and contributing to exercise sessions

Written

### In the programs

• Semester
Fall
• Exam form
Written
• Credits
4
• Subject examined
Probabilities and statistics I
• Lecture
2 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks
• Passerelle HES - SIE, 2020-2021, Autumn semester
• Semester
Fall
• Exam form
Written
• Credits
4
• Subject examined
Probabilities and statistics I
• Lecture
2 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks

### Reference week

MoTuWeThFr
8-9
9-10
10-11
11-12
12-13
13-14  CM1
14-15
15-16  CM1
16-17
17-18
18-19
19-20
20-21
21-22

Lecture
Exercise, TP
Project, other

### legend

• Autumn semester
• Winter sessions
• Spring semester
• Summer sessions
• Lecture in French
• Lecture in English
• Lecture in German